Machine Learning and Big Data Processing: A Technological Perspective and Review

Abstract

This paper discusses the role of Machine Learning (ML) based algorithms and methods in Big Data Processing & Analytics (BDA). ML and BDA are both evolutionary fields of computing and the developments in these fields are complementing each other. The ever changing data landscape in modern digital world have resulted in newer ways of data processing frameworks in order to get meaningful insights which are unprecedented. This paper presents a detailed review on latest developments in ML algorithms for Big Data Processing. In later section key challenges associated with application of ML based approaches are also discussed. ML based Big Data Processing has gained popularity and new developments are on the rise for efficient data processing. This field is witnessing unparalleled emergence of new methods and approaches for efficient data processing in order to discover interestingness for decision making. Thus, more and more ML based data processing approaches are being used for Big Data Processing. With the splurge data from different newer sources, heterogeneous nature of data, uncertain & unstructured data, the so called Big Data with all its characteristics (5 Vs) there is an ever increasing need to use approaches which aid in modelling and processing of these data, provide automated approach to data processing and so on. These type of new processing requirements have given a big boost to the development of new ML based methods for managing & processing them. The paper will be useful to the scholars who are researching in this interesting & challenging domain of ML and Big Data Processing.